We live in an information culture. We are accustomed to having information instantly available and accessible, along with feedback and recommendations. We want to know what people think and like (or dislike). We want to know how we compare with "others like me." Just as analytics powers Amazon.com, Netflix, TheRestaurantFinder.com, and Yelp, it can support tools for student empowerment.
"This course will provide a generally non-technical introduction to learning analytics and how they are being deployed in various contexts in the education field. Additionally, the tools and methods, ethics and privacy, and systemic impact of analytics will be explored, presenting a broad overview of the current state and possible future directions of the field.
Capturing and analyzing data has changed how decisions are made and resources are allocated in the fields of business, journalism, government, military, and intelligence. Through better use of data, leaders are able to plan and enact strategies with greater clarity and confidence. Data is a value point that drives increased organizational efficiency and a competitive advantage. Analytics provide new insight and actionable intelligence. Companies such as Microsoft, IBM, Google, and Amazon are investing heavily in technologies and techniques to help individuals and organizations make sense of and unlock the value within big data..."
Analytics has become a hot topic in the educational community, and several key questions must be addressed concerning the infrastructure of an analytics program. These issues include the systems and tools used for analytics, data sources and models, and governance structures. This research bulletin broadly addresses these functions and related activities of the IT department that are important to providing analytics infrastructure.
Analytics in Higher Education: Benefits, Barriers, Progress, and Recommendations
The objectives of this research were to assess the current state of analytics in higher education, outline the challenges and barriers to using analytics, and develop a maturity index to provide a common means of assessing progress in analytics.
The purpose of this study was to examine correlates of both online classroom community and student engagement in online learning, as well as to compare community and engagement across disciplines in higher education. Participants (n=1,410) in online courses across five colleges and in both graduate and undergraduate courses were asked to complete an online survey. The survey consisted of 23 items measuring community and engagement as well as an additional six demographic items. Factor analysis yielded the following three factors accounting for approximately 58% of the total variance: classroom community with instructors (eight items), classroom community with classmates (eight items), and engagement in learning (seven items).
I chose “data” as one of the top trends of 2011, and the opening line of that article reads “If data was an important trend for 2011, I predict it will be even more so in 2012.” Indeed. There’s a great deal that happened in 2012 that’s a continuation of what we saw last year — enough that I could probably just copy-and-paste from the article I wrote back then:
Although states are doing a masterful job of accumulating data and integrating data sources to support education improvement, according to a new report, the next part of the job may be their toughest yet: teaching people how to use the data.
Denver — Data mining is creeping into every aspect of student life—classrooms, advising, socializing. Now it’s hitting textbooks, too.
CourseSmart, which sells digital versions of textbooks by big publishers, announced on Wednesday a new tool to help professors and others measure students’ engagement with electronic course materials.
When students use print textbooks, professors can’t track their reading. But as learning shifts online, everything students do in digital spaces can be monitored, including the intimate details of their reading habits.
So where will online growth come from? A report last week from Moody’s indicated that massive open online courses (MOOCs) represent a “pivotal development” in higher education and could revolutionize the industry.
A ton of educational innovations are coming down the pike as a result of big data, which effectively turns “learning” – heretofore somewhat ineffable – into a living, breathing body that can be monitored: closer to medicine than education has ever been.
It is for this reason – the “massive” element – that MOOCs may prove to be important. With mass comes big data. And with big data comes better product and engagement of traditional age students. But massive courses aren’t the only path to big data. Smaller courses with much higher completion rates could prove to be a better source of data.
Regardless, in the coming years education research will allow us to check the two hard boxes: product and engagement of traditional age students. Real growth for online education – what we call Online Education 2.0 – will come when we’re firing on all four cylinders, not just two.
There’s big talk these days about “big data” in education—looking for patterns of behavior as students click through online classrooms and using the insights to improve instruction. One start-up company that manages online discussion forums for thousands of courses recently performed its first major analysis of behavioral trends among students, and found what its leaders say amounts to advice for instructors.
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